Early in the movie “Moneyball,” the Oakland Athletics scouting team discusses the qualities of potential ballplayers to replace three stars lost to free agency. “He’s got a baseball body,” one says. “He’s got a beautiful swing,” says another, “the ball pops off the bat.” “He’s got a great glove.” “He’s got the right attitude.”

In another scene, Yale educated economist and decidedly nonathletic Peter Grant tells the A’s general manager, Billy Beane, that’s medieval thinking. “Your goal shouldn’t be to buy players; your goal should be to buy wins,” he says. Grant supports his premise with a complicated algorithm of statistical analysis that can identify value in players that other teams overlook. The key metric: can they get on base?

“It turns out that baseball and oil and gas aren’t that different,” said Andrea Passman, Consol Energy Inc. vice president of development, at Hart Energy’s DUG East conference in Pittsburgh recently. She compared Consol’s current corporate and operational strategy to the same concepts portrayed in Moneyball.

In the oil and gas ballgame, “Everyone is still talking about the old math, of what makes a great play,” she said. “It’s an imperfect understanding of where value—or ‘wins’—come from.

“Who cares if it’s the thickest rock on earth or if you got the acreage at a total bargain? If it takes years to get a permit or you spend too much on proppant or you can’t get to market, does it really drive value?”

We’ve all heard the idea of Big Data thrown around, and while some have experimented, few have embraced it. Consol is all in.

Three years ago when the Pittsburgh-based producer made the strategic decision to split off its coal assets and become a pure-play Appalachian E&P, well results fell into the bottom quartile. Newly appointed CEO Nick DeIuliis decided it didn’t have the time to play catch-up to the rest of the industry with traditional trial-and-error methodology, Passman said.

When changing one variable at a time, finding the right method can be costly and time consuming.

“The field is an expensive laboratory,” she said. “We’re basically a 153-year-old start-up company today, and we had to come up with a new way to get ahead of the other players. So we turned to cutting-edge technology and modeling analytics to slingshot ourselves ahead. We had to play Moneyball.”

First, Consol leveraged its nonoperated program across its vast acreage position to develop a detailed earth model combining data from 197 wells—logs, core, microseismic, production, etc. “We built it because a human can’t wrap their mind around that much information. It allowed us to participate in everyone else’s experiments.”

Next, it added reservoir and frack models to the mix and built prototypes from those. “We threw our cookie-cutter designs straight out the window.”

The first experiment: The Gaut 4IH in Westmoreland County, Pa., targeting deep Utica. The Gaut IP’d at 61 million cubic feet per day (MMcf/d) and two years later sports an EUR of 3.5 billion cubic feet per 1,000 lateral feet. It’s the second-best Utica producer to date and one of the best gas wells in North America.

“It was the model that told us to go get the value in Westmoreland County. It was the model that gave us new insight to interpret and differentiate. We can see answers in the data that we couldn’t see before, and then we applied them in the field.

“We utilize the model to surface hidden relationships, to predict behavior in a complex, heterogeneous system like the reservoir. What was impossible is now possible.”

The prototypes are designed to reveal value quickly, to react and adjust from the data of a single well vs. many, saving months or years of experimenting.

“Once you have a single data point, you can build your model off of that and then play with all the variables to see what the performance is going to look like. We can update immediately.”

Using the models, Consol’s capital efficiency has rocketed from 1.2 Mcfe per dollar in 2014 to 2.8 today, more than doubling the production per dollar spent. Average EURs are up 100%. Today, Consol drills half as many wells as in 2014—with twice the production. “Our rate of change is profound,” said Passman.

Tie the other analytic models to Consol’s portfolio model, and the operational actions directly link to the financial metrics driving the company’s capital allocation.

“Now we’re making actionable decisions that drive NAV based on prescriptive analytics. It lets us understand the impact on financials almost in real time.”

Two Aiken wells will directly offset the Gaut, using an improved model from Gaut data. Results will be released later this year. “We’re going straight into development off of three wells,” Passman said. The analytics model “is a game-changer in terms of time and understanding.”

Since implementing the data driven models, Consol’s breakevens have dropped from $3.50 to $1.77/Mcf. Sounds like a winning strategy

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